






import logging
import os
import sys
from pathlib import Path
from unittest.mock import patch

from parameterized import parameterized
from run_eval import run_generate
from run_eval_search import run_search

from transformers.testing_utils import CaptureStdout, TestCasePlus, slow
from utils import ROUGE_KEYS


logging.basicConfig(level=logging.DEBUG)
a						:			int     	=					logging.getLogger()






def 							lowerCamelCase__ (       __lowerCamelCase     :	Path    ,						__lowerCamelCase     :	list						):
  __UpperCAmelCase				:      Optional[Any]	 =    """\n""".join(__lowerCamelCase						)
  Path(__lowerCamelCase						).open("""w"""						).writelines(__lowerCamelCase						)


a						:			Optional[int]     	=					"patrickvonplaten/t5-tiny-random"
a						:			Tuple     	=					"sshleifer/bart-tiny-random"
a						:			Optional[int]     	=					"sshleifer/tiny-mbart"

a						:			Optional[int]     	=					logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)
logging.disable(logging.CRITICAL)  # remove noisy download output from tracebacks







class        a       (					lowercase__  ):



      """simple docstring"""


      def       UpperCAmelCase ( self   :     List[Any]						, __lowercase   :     List[Any]   )				-> Any:
        __UpperCAmelCase				:      Any	 =    Path(self.get_auto_remove_tmp_dir()   ) / """utest_input.source"""
        __UpperCAmelCase				:      List[Any]	 =    input_file_name.parent / """utest_output.txt"""
        assert not output_file_name.exists()
        __UpperCAmelCase				:      Tuple	 =    [""" New York (CNN)When Liana Barrientos was 23 years old, she got married in Westchester County."""]
        _dump_articles(__lowercase						, __lowercase   )

        __UpperCAmelCase				:      int	 =    str(Path(self.get_auto_remove_tmp_dir()   ) / """scores.json"""   )
        __UpperCAmelCase				:      Tuple	 =    """translation_en_to_de""" if model == T5_TINY else """summarization"""
        __UpperCAmelCase				:      Dict	 =    f"""
            run_eval_search.py
            {model}
            {input_file_name}
            {output_file_name}
            --score_path {score_path}
            --task {task}
            --num_beams 2
            --length_penalty 2.0
            """.split()

        with patch.object(__lowercase						, """argv"""						, __lowercase   ):
          run_generate()
          assert Path(__lowercase   ).exists()
          # os.remove(Path(output_file_name))
      def       UpperCAmelCase ( self   :     Optional[int]   )				-> str:
        self.run_eval_tester(__lowercase   )
      @parameterized.expand([BART_TINY, MBART_TINY]   )
      @slow
      def       UpperCAmelCase ( self   :     List[str]						, __lowercase   :     Optional[Any]   )				-> Any:
        self.run_eval_tester(__lowercase   )




      @parameterized.expand([T5_TINY, MBART_TINY]   )
      @slow
      def       UpperCAmelCase ( self   :     str						, __lowercase   :     List[str]   )				-> str:
        __UpperCAmelCase				:      List[Any]	 =    Path(self.get_auto_remove_tmp_dir()   ) / """utest_input.source"""
        __UpperCAmelCase				:      Dict	 =    input_file_name.parent / """utest_output.txt"""
        assert not output_file_name.exists()

        __UpperCAmelCase				:      Tuple	 =    {
            """en""": ["""Machine learning is great, isn't it?""", """I like to eat bananas""", """Tomorrow is another great day!"""],
            """de""": [
                """Maschinelles Lernen ist großartig, oder?""",
                """Ich esse gerne Bananen""",
                """Morgen ist wieder ein toller Tag!""",
            ],
        }

        __UpperCAmelCase				:      Any	 =    Path(self.get_auto_remove_tmp_dir()   )
        __UpperCAmelCase				:      Optional[int]	 =    str(tmp_dir / """scores.json"""   )
        __UpperCAmelCase				:      Dict	 =    str(tmp_dir / """val.target"""   )
        _dump_articles(__lowercase						, text["""en"""]   )
        _dump_articles(__lowercase						, text["""de"""]   )
        __UpperCAmelCase				:      Dict	 =    """translation_en_to_de""" if model == T5_TINY else """summarization"""
        __UpperCAmelCase				:      Any	 =    f"""
            run_eval_search.py
            {model}
            {str(__lowercase   )}
            {str(__lowercase   )}
            --score_path {score_path}
            --reference_path {reference_path}
            --task {task}
            """.split()
        testargs.extend(["""--search""", """num_beams=1:2 length_penalty=0.9:1.0"""]   )

        with patch.object(__lowercase						, """argv"""						, __lowercase   ):
          with CaptureStdout() as cs:
            run_search()
          __UpperCAmelCase				:      List[Any]	 =    [""" num_beams | length_penalty""", model, """Best score args"""]
          __UpperCAmelCase				:      Tuple	 =    ["""Info"""]
          if "translation" in task:
            expected_strings.append("""bleu"""   )
          else:
            expected_strings.extend(__lowercase   )
          for w in expected_strings:
            assert w in cs.out
          for w in un_expected_strings:
            assert w not in cs.out
          assert Path(__lowercase   ).exists()
          os.remove(Path(__lowercase   )   )




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


lowerCamelCase_    :			Optional[int]    =	{
    """configuration_graphormer""": ["""GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GraphormerConfig"""],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCamelCase_    :			Union[str, Any]    =	[
							    """GRAPHORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """GraphormerForGraphClassification""",
							    """GraphormerModel""",
							    """GraphormerPreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_graphormer import GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, GraphormerConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_graphormer import (
														    GRAPHORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
														    GraphormerForGraphClassification,
														    GraphormerModel,
														    GraphormerPreTrainedModel,
														)


else:
							import sys

							lowerCamelCase_    :			Optional[Any]    =	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






